Conventional formation evaluation methods for detecting hydrocarbons have relied largely on electrical log measurements of either formation resistivity or conductivity and on measurements of formation porosity from neutron, density or sonic tool measurements. The utility of electrical log measurements for hydrocarbon detection, and also for quantitative estimation of hydrocarbon saturations, is dependent on empirically based saturation equations like the well known Archie equation or others including the Waxman-Smits and Dual-Water models. In many environments this traditional approach to formation evaluation provides accurate reservoir predictions. Nonetheless, the following types of occurrences are not uncommon: missed pay zones, inaccurate estimates of hydrocarbons in place and costly completions of zones that are not commercial. The causes of these occurrences include formation waters of unknown or variable salinity, fresh formation waters, clay conductance effects on measured resistivity, inaccurate inversion of resistivity data, and formations that have anomalous values for the Archie parameters.
The evaluation of hydrocarbon reservoirs using pulsed NMR logging tools offers the potential to provide a solution to the problem in formnation evaluation stemming from the fact that many hydrocarbon reservoirs can be misinterpreted or even missed altogether by conventional resistivity based evaluation methods.
An NMR approach that uses a "differential methodology" was proposed in publications of Akkurt, et al. (NMR Logging Of Natural Gas Reservoirs, Paper N presented at the 36.sup.th Annual Meeting of the Society of Professional Well Log Analysts, 1995). This methodology involves making two NMR spin-echo measurements with different wait times; that is, different times for polarization or re-polarization of the spins. The raw measurements (detected spin echo signals), or the T.sub.2 -distributions computed from these measurements, are subtracted to yield a "differential signal" (either a differential T.sub.2 spectrum or echo train) that can be further processed to estimate hydrocarbon filled porosity. In the NMR well logging literature, some of the differential methods are called differential spectrum method (DSM) and time domain analysis (TDA). The wait times of the methods are selected so that the differential signal contains small contributions from the brine in the formation. In order to select proper wait times so that the brine contribution is canceled, knowledge of the NMR properties of the fluids in the formation is required. This is a limitation of these methods for oil exploration logging. Moreover, the interpretation of the technique requires that the T, distribution of the brine phase not overlap with the T.sub.1 spectra of the hydrocarbon phases. In carbonate reservoirs and in reservoirs containing light to intermediate viscosity oils (e.g., 1-50 cp), the brine and hydrocarbon TI-distributions can overlap. This limits the applicability of the differential methods to shaly sands containing very low viscosity oils and gas. A recent paper, Akkurt et al. (Enhanced Diffusion: Expanding the Range of NMR Direct Hydrocarbon-Typing Methods, Paper GG presented at the 39.sup.th Annual Meeting of the Society of Professional Well Log Analysts, 1998) noted the limitations of the DSM and TDA methods for oils with intermediate viscosities and proposed a method called the Enhanced Diffusion Method (EDM) that attempts to exploit the fact that the brine phase is more diffusive than intermediate viscosity oils. By increasing the echo spacing so that diffusion dominates the T.sub.2 relaxation of the brine, an upper limit (T.sub.2DW) on the apparent T.sub.2 can be achieved. To obtain the oil filled porosity, the Akkurt, et al. 1998 paper proposed integrating the apparent T.sub.2 -distribution for relaxation times greater than T.sub.2WD. Although the basic concept of the EDM is believed to be valid, there are complications in practice that limit its reliability for detection of oil, including: (1) the apparent T.sub.2 -distributions are broadened by the regularization (smoothing) that is applied by the processing to reduce noise artifacts, so integrating the apparent T.sub.2 -distributions from a sharp brine cutoff can lead to predictions of oil in water zones; (2) the oil signal can have a short relaxation time tail that extends into the brine signal; (3) in exploration wells it cannot be assumed that the diffusivity of formation oils is less than that of water; and (4) in wells drilled with oilbase muds, it is difficult using the EDM concept to separate the filtrate signal from that of the native oil.
A recent paper by Chen et al. (Estimation of Hydrocarbon Viscosity With Multiple TE Dual Wait-Time MRIL Logs, Paper 49009 in the Transactions of the 1998 SPE Annual Technical Conference and Exhibition, 1998), proposes a method for combining dual-wait time and multiple echo spacing data to estimate oil viscosity. The differential methodology is used to combine the different measurements. The spin-echo trains from long and short wait time data acquired with the same echo spacing are subtracted to eliminate the water brine signal. This method has the limitations discussed above. Furthermore, the subtraction of the differential signal increases the noise by a factor of 1.4 which is also one of the drawbacks of the TDA method.
A fundamental weakness of the aforementioned inversion methods is that separation of the measured data into brine and hydrocarbon signals is only done in an ad hoc manner in fitting the differential signal. An approach that makes this separation at the outset is disclosed in Looyestijn (Determination of Oil Saturation from Diffusion NMR Logs, Paper SS presented at the 37th Annual Meeting of the Society of Professional Well Log Analysts, 1996), which uses "diffusion processing" to compute the oil saturation from NMR data acquired with different echo spacings. Looyestijn fits the measured data to a model that explicitly includes the brine and oil signals. The model used five simple exponentials for the brine phase and a stretched exponential for the oil phase and was applied to NMR log data from a development well drilled with a waterbase mud. The oil relaxation times were known from lab measurements on produced samples and the oil and brine filled porosities were computed from the log data. In a Published PCT International Patent Application further describing the work of Looyestijn and his colleagues (WO 97/34166 of R. Bonnie, M. Johannes, P. Hofstra, W. Looyestijn, , R. Sandor and J. Karl), there is disclosed a technique for determining the fraction of a fluid selected from at least two fluids in a formation that includes the following steps: selecting a relationship between the NMR echo response from the fluids, the fractions of the fluids, and at least one variable which affects the NMR echo response in a manner dependent on the fractions of the fluids, varying the at least one variable, such as wait time or pulse spacing, in the course of an NMR measurement to thereby affect the NMR echo response in a manner dependent on the fractions of the fluids, and determining the fraction of the selected fluid by fitting the NMR echo response to the selected relationship. An example set forth in WO 97/34166 involves the determination of water saturation in a rock formation containing a medium gravity oil and water by applying a gradient magnetic field NMR measurements on a sample of the rock formation. The water was modeled with two transverse relaxation times and two corresponding volume fractions, the component with the short relaxation time representing bound water and the component with the long relaxation time representing movable water. The oil was modeled by one transverse relaxation time and one corresponding volume fraction. The WO 97/34166 Publication states that by repeating their method for a range of practical values for the water and oil parameters, it was found that the method according to their invention is only weakly dependent on the actual values of the oil parameters. If no information on these parameters is available, the Publication states that errors in estimated water saturation may be up to 0.1. It further states that if the oil viscosity can be estimated at an accuracy of two decimals, the resulting error in water saturation is negligible compared to the overall accuracy of the measurement. Thus, in this technique, which models oil with one transverse relaxation time with a corresponding volume fraction, prior knowledge of oil viscosity is apparently needed to obtain adequate accuracy. In well logging practice, prior knowledge of the in situ oil viscosity is usually not known. The Bonnie, et al. technique further requires an input for the brine T1/T2 ratio. This quantity is variable and unknown so that a proper value cannot be generally input. The result of inaccuracies in the input T1/T2 ratio can lead to errors in the fluid amplitudes estimated by this technique. In summary, the prior methods lack a coherent theoretical and operational framework needed to provide an accurate and complete NMR based formation evaluation. It is among the objects of the present invention to provide an improved formation evaluation technique that overcomes limitations of prior art techniques.